I use the limma package to analyze the data, extract the genetic differences, but in the list of results, adj.p.value are basically the same, which is why, with the same code, analysis of other data, it did not encounter this problem, it is the problem of data. 

Here are the results of  data analyzed using the code ：

 Here is the code I use：

 library(affy)
AffyRawData<-ReadAffy(widget=TRUE)
data.class(AffyRawData)
par(mfrow=c(2,3))
image(AffyRawData[,c(1,2,3,4,5,6)])
library(simpleaffy)
Data.qc<-qc(AffyRawData)
plot(Data.qc)
library(RColorBrewer)
library(affyPLM)
Pset<-fitPLM(AffyRawData)
colors<-brewer.pal(12,"Set3")
Mbox(Pset,ylim=c(-1,1),col=colors,main="RLE",las=3)
boxplot(Pset,ylim=c(0.95,1.22),col=colors,main="NUSE",las=3)
data.deg<-AffyRNAdeg(AffyRawData)
plotAffyRNAdeg(data.deg,col=colors)
legend("topleft",rownames(pData(AffyRawData)),col=colors,lwd=1,inset=0.05,cex=0.5)
AffyRawDatarma<-rma(AffyRawData)
boxplot(AffyRawDatarma,col=colors,las=3,main="RMA")
library(limma)
eset<-exprs(AffyRawDatarma)
design <- model.matrix(~ 0+factor(c(1,1,1,2,2,2)))
colnames(design) <- c("group1", "group2")
contrast.matrix <- makeContrasts(contrasts="group2-group1",levels=design)
design
fit <- lmFit(eset, design)
fit1<- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit1)
dif<-topTable(fit2,coef="group2-group1",n=nrow(fit2),lfc=log2(1.5))
dif<-dif[dif[,"P.Value"]<0.05,]
head(dif)

Is there anyone who can help me explain this problem? Thank you very much 

This isn't a problem -- it just means there are no significantly differentially expressed genes.

Sorry, I don't understand. You mean the difference is very small, right? I can't use adj.p.value as a filter condition. Should I use P.Valve? Thanks very much